On the Impact of a Small Initial Population Size in the IPOP Active CMA-ES with Mirrored Mutations on the Noiseless BBOB Testbed

Dimo Brockhoff 1 Anne Auger 2 Nikolaus Hansen 2
1 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
2 TAO - Machine Learning and Optimisation
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : Active Covariance Matrix Adaptation and Mirrored Mutations have been independently proposed as improved variants of the well-known optimization algorithm Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for numerical optimization. This paper investigates the impact of the algorithm's population size when both active covariance matrix adaptation and mirrored mutation are used in the CMA-ES. To this end, we compare the CMA-ES with standard population size $\lambda$, i.e., $\lambda = 4 + \lfloor 3\log(D) \rfloor$ with a version with half this population size where $D$ is the problem dimension.
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Dimo Brockhoff, Anne Auger, Nikolaus Hansen. On the Impact of a Small Initial Population Size in the IPOP Active CMA-ES with Mirrored Mutations on the Noiseless BBOB Testbed. GECCO Companion '12, Jul 2012, Philadelphia, PA, United States. pp.285-290, ⟨10.1145/2330784.2330825⟩. ⟨hal-00746122⟩

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